CN113391615A - Variable time pulse algorithm for probability statistics - Google Patents

Variable time pulse algorithm for probability statistics Download PDF

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Publication number
CN113391615A
CN113391615A CN202110506090.1A CN202110506090A CN113391615A CN 113391615 A CN113391615 A CN 113391615A CN 202110506090 A CN202110506090 A CN 202110506090A CN 113391615 A CN113391615 A CN 113391615A
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time
pulse
feedforward
time interval
optimal
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CN113391615B (en
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李珂
刘永红
周小朋
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Northwest Electric Power Research Institute of China Datang Corp Science and Technology Research Institute Co Ltd
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    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B23/00—Testing or monitoring of control systems or parts thereof
    • G05B23/02—Electric testing or monitoring
    • G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
    • G05B23/0218—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults
    • G05B23/0243—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults model based detection method, e.g. first-principles knowledge model
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F22—STEAM GENERATION
    • F22B—METHODS OF STEAM GENERATION; STEAM BOILERS
    • F22B35/00—Control systems for steam boilers
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B2219/00—Program-control systems
    • G05B2219/20—Pc systems
    • G05B2219/24—Pc safety
    • G05B2219/24065—Real time diagnostics

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  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Automation & Control Theory (AREA)
  • Chemical & Material Sciences (AREA)
  • Combustion & Propulsion (AREA)
  • Thermal Sciences (AREA)
  • Mechanical Engineering (AREA)
  • General Engineering & Computer Science (AREA)
  • Control Of Steam Boilers And Waste-Gas Boilers (AREA)

Abstract

The invention discloses a variable time pulse algorithm of probability statistics, which is used for carrying out optimization calculation on a pulse time function block in a main control optimization method of a stop-grinding pre-judging boiler based on the probability statistics.

Description

Variable time pulse algorithm for probability statistics
Technical Field
The invention belongs to the technical field of boiler control, and relates to a variable time pulse algorithm for probability statistics.
Background
In the process of frequent change of the load of the thermal power generating unit, when the AGC instruction of a power grid side requires load reduction of the thermal power generating unit, along with reduction of the load of the unit, when the load of the unit is reduced to a working condition that the grinding unit needs to be stopped, firstly, the coal feeding rate of a coal feeder of the grinding unit is reduced in a step-type manner at a certain speed from the current coal feeding rate, after the coal feeding rate of the coal feeder is reduced to the grinding unit stop buffer coal feeding rate, the coal feeding rate of the coal feeder is kept to continue to operate for about 1min under the working condition of the grinding unit stop buffer coal feeding rate, the coal feeding rate of the coal feeder is reduced to 0t/h, and then the coal feeder is stopped. After the coal feeder stops running, the coal mill and a hot primary air door of the coal mill are stopped and closed after delaying for about 2min, so that all pulverized coal cached in the inertia of the coal mill is ensured to be blown into a hearth, the occurrence of deflagration accidents caused by coal accumulation when a next grinding group is started is prevented, but the pulverized coal cached in the inertia of the coal mill enters the hearth to be combusted, the main steam pressure is directly increased in the load reduction process and even exceeds the safety value of the main steam pressure, and the safety and the stable running of a unit are seriously influenced.
The method comprises the steps of researching the grinding process and rule of operators by grinding stop and prejudgment boiler master control feedforward of probability statistics, abstracting the grinding stop and prejudgment boiler master control feedforward of probability statistics, and combining the change of main steam pressure deviation to dynamically adjust the amplitude, zero return time and zero return rate of the grinding stop and prejudgment boiler master control feedforward of probability statistics in real time, thereby comprehensively adjusting the change of main steam pressure in the load reduction grinding process.
In the stop-run pre-judging boiler main control feedforward optimization method based on probability statistics, the setting of pulse time plays a crucial role in the optimization effect, a variable-time pulse algorithm system based on probability statistics comprehensively calculates the optimal pulse time of a pulse function block in stop-run pre-judging boiler main control feedforward through the ideas of big data acquisition, data classification and probability statistics, fundamentally ensures the magnitude effect of the feedforward magnitude effect, and avoids the problem that the feedforward magnitude effect cannot meet the actual requirement of the system due to the change of the system working condition.
Disclosure of Invention
The invention aims to provide a variable time pulse algorithm for probability statistics, which solves the problem that the effect of feedforward quantity value action cannot meet the actual requirement of a system due to the change of the working condition of the system in the prior art.
The technical scheme adopted by the invention is that a variable time pulse algorithm of probability statistics is implemented according to the following steps:
step 1, data acquisition: defining a circle as a period, and acquiring a pulse time value t in each feedforward triggering process according to the periodnAnd the maximum value P of the absolute value of the deviation between the main steam pressure set value and the main steam pressure measured value in the time period from the feed-forward trigger to the feed-forward zero-returningmax；
Step 2, data statistics: counting the statistics of each of all the equidistant sections in one periodFeedforward trigger times deltan；
Step 3, data screening and calculation: according to deltanAnd PmaxAveraging T of pulse times within an optimal time intervalAre all made ofI.e. as the optimum pulse trigger time for the next cycle.
The invention is also characterized in that:
collecting the pulse time value t in each feedforward triggering processnThe method comprises the following specific steps:
step a, dividing the total pulse triggering time interval into n equidistant intervals, wherein the interval time of the equidistant intervals is the same, and obtaining n pulse time values t after each feedforward triggeringn；
B, using set to calculate the pulse time t in each feedforward triggering processnAnd (4) showing.
The total pulse triggering time interval of the step a is 120 s-180 s, the number n of equidistant intervals is 6, and the 6 equidistant intervals are t1、t2、t3、t4、t5、t6Equidistant intervals are 10s apart.
The set of steps b is:
Figure BDA0003058443360000032
step 3 is specifically implemented according to the following steps:
step 3.1, determining an optimal time interval;
step 3.2, marking the pulse triggering times delta in the optimal time intervaln0Calculating the time sum t 'of all trigger pulses in the optimal time interval'nAs shown in formula (2):
Figure BDA0003058443360000031
step 3.3, solving the average value T of the pulse time in the optimal time intervalAre all made ofAs shown in formula (3):
Tare all made of＝t’n/δn0 (3)
For deltanAfter sorting according to the sequence from big to small, taking deltanMaximum and maximum value P of the absolute value of the deviation between the steam pressure set value and the main steam pressure measured valuemaxThe time interval within | + -0.3 Mpa is the optimal time interval.
The invention has the beneficial effects that:
1. the method carries out optimization calculation on the pulse time function block in the main control optimization method of the boiler based on the probability statistics and the stop-grinding prejudgment.
2. The invention comprehensively calculates the optimal pulse time of the pulse function block in the main control feed-forward logic of the boiler for wear-stopping prejudgment through the ideas of big data acquisition, data classification and probability statistics,
3. the invention fundamentally ensures the magnitude effect of the feedforward magnitude action and avoids the problem that the feedforward magnitude action effect cannot meet the actual requirement of the system due to the change of the working condition of the system.
Detailed Description
The present invention will be described in detail with reference to the following embodiments.
Example 1
The invention relates to a variable time pulse algorithm for probability statistics, which is implemented by the following steps:
step 1, data acquisition: defining one cycle as a time period, feeding forward the minimum time t of trigger pulse in the first cycle of embodiment 1min121s, maximum value tmax178s, the total interval of pulse trigger time is 120-180 s based on the division, and the interval is divided into 6 equidistant intervals t1、t2、t3、t4、t5、t6Each interval is 10s, and the pulse time value t in each feedforward triggering process is integratednRepresented by formula (1):
Figure BDA0003058443360000041
step 2, counting each of 6 equidistant intervals in a periodNumber of successful pulse triggers δ1、δ2、δ3、δ4、δ5、δ6。
Step 3.1, data screening and calculation: for delta1、δ2、δ3、δ4、δ5、δ6After sorting according to the order from big to small, the maximum delta is takennAnd the maximum value P of the absolute value of the deviation between the set value of the steam pressure and the measured value of the main steam pressuremaxThe time interval within | + -0.3 Mpa is the optimal time interval.
Step 3.2, marking the pulse triggering times delta in the optimal time intervaln0Calculating the time sum t 'of all trigger pulses in the optimal time interval'nAs shown in formula (2):
Figure BDA0003058443360000051
step 3.3, solving the average value T of the pulse time in the optimal time intervalAre all made ofAs shown in formula (3):
Tare all made of＝t’n/δn0 (3)
And 4, returning data: mean value T of the pulse time in the optimum time intervalAre all made ofFor optimal pulse time in the current period, the time average value TAre all made ofAnd inputting the time-variable pulse block TP to dynamically optimize the time parameter.
And 5, data analysis: and analyzing the abnormal interval (the pulse triggering time is less than or equal to 3 times or the maximum value of the absolute deviation value between the main steam pressure set value and the main steam pressure measured value is greater than 1.0 MPa) to provide a basis for judging whether the coal mill and the coal feeder have abnormal working condition points such as equipment body faults, whether the operation of operators is appropriate, whether the coal quality is violent in fluctuation and the like.

Claims (6)

1. A variable time pulse algorithm of probability statistics is characterized by being implemented according to the following steps:
step 1, data acquisition: define oneThe period is one period, and the pulse time value t in each feedforward triggering process is acquired according to the periodnAnd the maximum value P of the absolute value of the deviation of the main steam pressure in the time period from the feedforward trigger starting to the feedforward zero returningmax；
Step 2, data statistics: counting the successful times delta of feedforward triggering in all equidistant sections in one periodn；
Step 3, data screening and calculation: according to said deltanAnd PmaxAveraging T of pulse times within an optimal time intervalAre all made ofI.e. as the optimal pulse trigger time in the next cycle.
2. The probabilistic statistical time-varying pulse algorithm of claim 1, wherein the pulse time t is collected for each feedforward triggernThe method comprises the following specific steps:
step a, dividing the total pulse triggering time interval into n equidistant intervals, wherein the interval time of the equidistant intervals is the same, and obtaining n pulse time values t after each feedforward triggeringn；
B, using set to calculate the pulse time t in each feedforward triggering processnAnd (4) showing.
3. The probabilistic variable time pulse algorithm according to claim 2, wherein the total pulse trigger time interval of step a is 120s to 180s, the number of equidistant intervals N is 6, and 6 of the equidistant intervals t is1、t2、t3、t4、t5、t6Equidistant intervals are 10s apart.
4. A probabilistic statistical time-varying pulse algorithm according to claim 3, wherein the set of steps b is:
Figure FDA0003058443350000011
Figure FDA0003058443350000021
5. the probabilistic statistical time-varying pulse algorithm according to claim 1, wherein the step 3 is specifically implemented according to the following steps:
step 3.1, determining an optimal time interval;
step 3.2, marking the pulse triggering times delta in the optimal time intervaln0Calculating the time sum t 'of all trigger pulses in the optimal time interval'nAs shown in formula (2):
Figure FDA0003058443350000022
step 3.3, solving the average value T of the pulse time in the optimal time intervalAre all made ofAs shown in formula (3):
Tare all made of＝t′n/δn0 (3)
6. A probabilistic statistical time-varying pulse algorithm as in claim 5, wherein δ is a pairnAfter sorting according to the order from big to small, the maximum delta is takennAnd the maximum value P of the absolute value of the deviation between the set value of the steam pressure and the measured value of the main steam pressuremaxThe time interval within | + -0.3 Mpa is the optimal time interval.
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